For many buyers of motor vehicles, safety features are an important factor in the purchasing decision, i.e., crash-worthiness of a motor vehicle plays an important role in establishing the quality of the motor vehicle, and thus, customer acceptance. Governmental regulations applicably to vehicle restraint systems requires robust restraint systems able to detect and protect a wide range of occupants in a variety of crash types. The automobile industry has come a long way in providing “smart” restraint systems. However, the current crash detection techniques are based on multi-stage sequential signal analysis algorithms and are generally tunes to detect specific types of crash events. The early detection of crash-events allows the parameters of vehicle restraint systems to be more accurately adjusted. Such parameters includes, but are not limited to, airbag inflation rates and pressures, and belt pre-tensioning systems.
The current crash sensing algorithms can be divided into two categories—speed dependent and crush dependent.
Speed dependent algorithms are based on variables related to speed, such as changes in speed (acceleration), jerk, speed, displacement, and/or energy.
Crush dependent algorithms use crush to predict the severity of the crash. Typically, there are one or more sensors mounted in the crush zone.
Furthermore, certain types of crashes pose other problems. For example, in the case of side impacts the space between the passenger(s) and side panels of the vehicles are much smaller and, thus, the required time to initiate the airbag are also much smaller.
To accommodate all of the different types of crashes, these algorithms are necessarily becoming more and more complex. Thus, the time involved in detecting a crash also increases which limits the effectiveness of the vehicle restraint system(s).
The present invention is aimed at one or more of the problems as set forth above.